A striking result is to show speedups over recent competition-winning SAT solvers in approximate optimization, since SAT solvers have been optimized and fine-tuned after decades of research and development. In contrast, the sIM is using a standard simulated annealing algorithm without any detailed fine-tuning. Further improvements using more sophisticated algorithms such as Parallel Tempering should increase the performance of the sIM. Moreover, experimental developments in emerging nanodevice technologies [1]}, [2]} such as Magnetic Tunnel Junction based asynchronous probabilistic computers [3]} can use the same architectural and algorithmic ideas we develop in this paper to provide additional speedup [4]}.
